NBA Early-Career Competition Analysis
Objective
Examine how rookie- and sophomore-year positional competition affects NBA lottery picks’ scoring trajectories over their first five seasons. Positional competition measures how crowded a player’s role is on their team.
Key Findings
★ Sophomore-year competition has the largest impact. Players with more positional competition in their second season start with slightly higher scoring averages but show flatter or even declining growth after Year 3.
★ Rookie-year competition has a modest effect. Higher competition in the first season slightly boosts baseline points per game but does not meaningfully alter scoring trajectories.
★ Early-career competition influences both short- and longer-term scoring development. While it may boost initial performance, it can limit growth later during a player’s early career.
Methods
Data: Player stats from Basketball Reference, cleaned and processed in Python and R.
Model: Linear mixed-effects model capturing player-level differences over time.
Validation: Confidence intervals and diagnostics ensured reliable estimates.
Visualization: Interactive plots of predicted scoring trajectories.
Why It Matters
The methods used here can be applied beyond sports analytics, in areas such as:
Finance: Modeling portfolio growth under varying conditions.
Healthcare: Tracking patient outcomes over time under different treatments.
Education: Evaluating student performance trajectories across learning environments.
Deep Dive
The full analysis, including data processing, model building, and detailed results is available: